3 research outputs found

    Minimum Symbol-Error Probability Symbol-Level Precoding With Intelligent Reflecting Surface

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    Transmission Design for Reconfigurable Intelligent Surface-Aided Wireless Systems

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    The performance benefits promised by Reconfigurable Intelligent Surface (RIS) are strongly dependent on the availability of highly accurate and up-to-date Channel State Information (CSI), which, however, is challenging to obtain. This thesis proposes efficient transceiver designs for a variety of CSI challenges such as worst channel condition in multicast systems, channel uncertainties caused by the presence of random blockages in millimeter wave systems, by the channel estimation error in downlink systems and by the presence of eavesdropper in security systems. First, a low-complexity transceiver design scheme in the multicast systems is proposed. In order to ensure the quality of service of the user with the worst channel condition, this thesis deploys an RIS to enhance signal coverage, and proposes two novel and efficient algorithms to jointly design the Base Station (BS) and RIS beamformings. The low-complexity algorithm with closed-form solutions is proved to have the same performance as the general second-order cone programming based algorithm. Second, novel fairness-oriented robust transceiver design schemes are proposed in RIS-aided millimeter wave systems. The channel uncertainty caused by the random blockages is analyzed, and the metric of maximum outage probability minimization is proposed. To address this problem, stochastic optimization techniques are adopted and closed-form solutions of the BS and RIS beamformings are then obtained. The proposed stochastic optimization algorithms are proved to converge to the set of stationary points. Third, a framework of robust transceiver design scheme is proposed to address the channel uncertainty caused by the cascaded BS-RIS-user channel estimation error. Two cascaded channel error models are analyzed, and the correspondingly two robust beamforming design problems are proposed. The optimization theory is used to address the complex non-convex optimization problems. The numerical results show that the proposed robust scheme can effectively resist channel uncertainty. Finally, robust transceiver design schemes are proposed in RIS-aided physical layer security systems. The schemes analyze the channel uncertainties caused by the eavesdropper who launches an active attack, and by the eavesdropper conducting passive eavesdropping. Numerical results show that the negative effect of the eavesdropper’s channel error is larger than that of the legitimate user
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